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AZURE Data-ware housing , Data-Bricks

Azure Data Warehousing Specialist

Responsibilities:
  • Designing and implementing cloud-based data warehouses.
  • Managing data storage solutions using Azure Synapse Analytics.
  • Ensuring efficient ETL (Extract, Transform, Load) processes.
  • Monitoring and optimizing data performance and security.
  • Collaborating with stakeholders to gather and analyze business requirements.
Skills:
  • Proficiency in Azure Synapse Analytics.
  • Strong understanding of data modeling and database design principles.
  • Knowledge of ETL tools (Azure Data Factory, SSIS).
  • Experience with SQL and T-SQL for querying and managing data.
  • Familiarity with data security best practices and Azure role-based access control.

Syllabus: Azure Data Warehousing

1. Introduction to Azure Data Warehousing
  • Overview of Cloud Data Warehousing.
  • Understanding Azure Synapse Analytics.
  • Benefits and Use Cases.
2. Data Modeling and Database Design
  • Basics of Data Modeling.
  • Star and Snowflake Schemas.
  • Designing Scalable and Secure Data Models.
3. Azure Synapse Analytics
  • Creating and Managing Workspaces.
  • Synapse SQL vs. Serverless SQL Pools.
  • Integrating Data with Azure Synapse Pipelines.
4. ETL and Data Integration
  • Building ETL Pipelines with Azure Data Factory.
  • Data Transformation using Mapping Data Flows.
  • Automating Workflows and Monitoring Pipelines.
5. Data Security and Performance
  • Role-Based Access Control (RBAC).
  • Data Encryption and Compliance in Azure.
  • Query Optimization and Indexing Techniques.
6. Advanced Reporting
  • Integrating Synapse with Power BI.
  • Creating Dashboards for Data Insights.
  • Real-time Analytics with Azure Stream Analytics.
7. Project Work
  • Designing a Scalable Data Warehouse.
  • Building ETL Pipelines for Real-world Scenarios.
  • Creating Reports and Dashboards with Power BI.

Databricks Specialist

Responsibilities:
  • Developing and maintaining data pipelines using Databricks and Spark.
  • Performing advanced data transformations and big data analysis.
  • Building machine learning models and integrating them into workflows.
  • Collaborating with data engineers and analysts for real-time analytics solutions.
  • Ensuring the scalability and performance of data pipelines.
Skills:
  • Expertise in Apache Spark and Databricks.
  • Strong Python, Scala, or R programming skills.
  • Proficiency in big data frameworks and distributed computing.
  • Familiarity with Delta Lake for data lake optimization.
  • Understanding of machine learning algorithms and MLOps.

Syllabus: Databricks

1. Introduction to Databricks
  • Understanding Unified Data Analytics.
  • Databricks Architecture and Key Components.
  • Setting up Workspaces in Azure Databricks.
2. Big Data Processing with Spark
  • Overview of Apache Spark.
  • Spark DataFrames and Datasets.
  • Working with RDDs.
3. Data Engineering with Databricks
  • Building Data Pipelines.
  • Writing ETL Jobs in Databricks.
  • Delta Lake for Optimized Data Storage.
4. Data Science and Machine Learning
  • Exploratory Data Analysis in Databricks.
  • Building Machine Learning Models with MLlib.
  • Integrating Databricks with Azure Machine Learning.
5. Advanced Databricks Features
  • Using Databricks Notebooks.
  • Real-time Streaming with Spark Structured Streaming.
  • Performance Optimization Techniques.
6. Collaboration and Security
  • Managing Workspace Permissions.
  • Sharing and Versioning Notebooks.
  • Securing Data in Databricks.
7. Project Work
  • Building and Deploying Data Pipelines.
  • Analyzing Big Data Sets with Spark.
  • Developing End-to-End Machine Learning Models.

This syllabus provides a comprehensive guide to learning Azure Datahousing And Databricks, covering foundational concepts, advanced techniques, and practical applications. If you need more detailed information or specific resources, feel free to ask!.

What is known as IT management?

IT management, or Information Technology management, involves overseeing all matters related to information technology operations and resources within an organization. It encompasses a broad range of responsibilities, including: Strategic Planning , IT Governance , Project Management , System and Network Administration , Security Management , IT Service Management , Resource Management , Performance Monitoring and Evaluation , Innovation and Adaptation , Overall, IT management is crucial for ensuring that an organization’s IT infrastructure is reliable, secure, and aligned with its strategic goals, thereby enabling the organization to operate efficiently and effectively.